Imposterism in Data Science: Addressing the credentials problem

We happen to talk a lot about the impostor syndrome these days. No wonder — it seems to be an important subject. But what is it? That feeling of faking it while others clearly know what’s they’re doing.

Many attempts have been made to clarify the issue. Explaining that it is OK, that we all feel that way going through life. Et cetera et cetera. Some advice has gone as far as making the impostor syndrome a badge of honor. But that’s on the extreme side, and I’ll save this topic for another time…

Today, I want to pick apart one particular advice on how to combat the feeling of being a fraud. That is, to roll up your sleeves and start learning. I’ve heard it many times before, and always wanted to respond, but never had the time. Because I was, you know, learning.

First off, I think this is a great advice in general. In fact, I typically follow somewhat similar guidelines in learning new things. But this in no way helps me combat my impostor syndrome.

Secondly, I must point out that the author does acknowledge his advice is not universal. Edwin says:

Now, what works for me might not work for you. Maybe a different system fits you better. However, I think everybody benefits from defining the data scientist he/she is and actively choose what not to learn. So, what I’m going to say next is not a disagreement with this approach, but rather an important addition that I feel is constantly overlooked.

Do you even PhD, bro?

There are jobs out there where your degree means everything. Lawyers and doctors are a good example of this category. And there are occupations where what matters the most is what you can do, while your degree (or lack of thereof) is a secondary issue at most.

Faking it in the world of educated people

If you think that this is a sound request, you won’t be wrong. But let me speak about it from my own experience. I’ve been in the workforce for 10 years, have been doing analytics for over 5 years. And I don’t have a degree. No, I don’t mean MS or PhD. I don’t have a Bachelor’s degree.

Yep. And it’s hard to admit. Ever since I had to leave one of the best Economics universities of my country for a full-time job to make ends meet, I felt ashamed of the fact that I never graduated. And the feeling became even stronger as I broke into the analytics / data science field. Whereas overall a Bachelor’s degree in combination with hard work and continuous learning is fairly enough to hold a well-paid job, in our field it is an absolute bare minimum, but you need much more.

So how do you think it feels when you come across a position you have all the skills for, but which requires an MS in Math, Computer Science or Statistics? You’re like “I’m 2 steps below that!” Or how does it feel when your direct report whom you teach, mentor and guide has a Master’s degree?

It doesn’t feel terrible. In fact, it feels just fine. But your impostor syndrome feeds off that.

No silver bullet

There aren’t many of us. Somehow, data science is different from even computer science. Credentials matter here. And most of the people do have at least a bare minimum of a Bachelor’s degree.

But for the small amount of folks like me, who work (or want to work) in analytics / data science, yet don’t have any degree beyond high school, here is some bitter truth: there is no silver bullet. Go and study formally.

All these ten years, I though I can prove the world wrong, thought I can show that one can be smart without a diploma from a 4-year university. MOOCs, online classes, free and paid resources, books, guides… It all takes you only so far.

And I’m tired of fighting this uphill battle. That’s why I’m starting again from ground zero. Getting an AA at a state college, followed by a BS and hopefully an MS at a state university. And we’ll see what’s next. Classes start next week. It’s going to be long and costly, but it’s going to be worth it.